code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def __UpperCamelCase( _A : i... | 614 | '''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMS... | 614 | 1 |
'''simple docstring'''
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 614 | '''simple docstring'''
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 614 | 1 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
requir... | 614 | '''simple docstring'''
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - gener... | 614 | 1 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
UpperCamelCase__ : str = '\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WI... | 614 | '''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky... | 614 | 1 |
'''simple docstring'''
UpperCamelCase__ : Any = range(2, 20 + 1)
UpperCamelCase__ : List[Any] = [10**k for k in range(ks[-1] + 1)]
UpperCamelCase__ : dict[int, dict[int, list[list[int]]]] = {}
def __UpperCamelCase( _A : str , _A : Union[str, ... | 614 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rand... | 614 | 1 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import Aut... | 614 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | 1 |
'''simple docstring'''
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
UpperCamelCase__ : str = False
class _lowercase ( unittest.TestCase ):
... | 614 | '''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__ : str = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __UpperCamel... | 614 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
@staticmethod
@abstractmethod
def lowerCAmelCase__ ( lowerCamelCase_ ) -> str:
'''simpl... | 614 | '''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOK... | 614 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCa... | 614 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ ... | 614 | 1 |
'''simple docstring'''
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
UpperCamelCase__ : Any = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 614 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : str = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'... | 614 | 1 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class _lowercase ( unittest.TestCase ):
'''simple docstring'''
def lowerCAmelCase... | 614 | '''simple docstring'''
import numpy as np
def __UpperCamelCase( _A : np.ndarray , _A : np.ndarray , _A : float = 1e-12 , _A : int = 1_00 , ):
'''simple docstring'''
assert np.shape(_A )[0] == np.shape(_A )[1]
# Ensure proper dimensiona... | 614 | 1 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __UpperCamelCase( _A : str , _A : complex , _A : str = "x" , _A : float = 10**-10 , _A : int = 1 , ):
'''simple docstring... | 614 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase ,low... | 614 | 1 |
'''simple docstring'''
from math import pi, sqrt, tan
def __UpperCamelCase( _A : float ):
'''simple docstring'''
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def __UpperCamelCase( _A : ... | 614 | '''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from tra... | 614 | 1 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def __UpperCamelCase( _A : list , _A : list , _A : list , _A : list... | 614 | '''simple docstring'''
import baseaa
def __UpperCamelCase( _A : str ):
'''simple docstring'''
return baseaa.baaencode(string.encode('''utf-8''' ) )
def __UpperCamelCase( _A : bytes ):
'''simple docstring'''
return baseaa.baadecode(_A ).decode('''utf-8''... | 614 | 1 |
'''simple docstring'''
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_ava... | 614 | '''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCamelCase__ : Optional[Any] = logging.getLogger(__name__)
Uppe... | 614 | 1 |
'''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def __UpperCamelCase( _A : np.ndarray , _A : tuple[int, int] , _A : tuple[int, int] , _A : bool , ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 614 | '''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCamelCase( _A : Any , _A : List[str]=() , _A : List[str]=None ... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase( _A : Callable[[int | float], int | float] , _A : int | float , _A : int | float , _A : int = 1_00 , ):
'''simple docstring'''
Up... | 614 | '''simple docstring'''
from __future__ import annotations
def __UpperCamelCase( _A : list[int] , _A : int , _A : int , _A : int ):
'''simple docstring'''
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[in... | 614 | 1 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCT... | 614 | '''simple docstring'''
def __UpperCamelCase( _A : float , _A : list[float] ):
'''simple docstring'''
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows list cannot be empty''' )
U... | 614 | 1 |
'''simple docstring'''
class _lowercase :
'''simple docstring'''
def __init__( self ,lowerCamelCase_ ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase__ : Union[str, Any] = n
UpperCAmelCase__ : List[Any] =... | 614 | '''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 614 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils... | 614 | '''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging... | 614 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Dict = {
'configuration_chinese_clip': [
'CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ChineseCLIPC... | 614 | '''simple docstring'''
from math import factorial, radians
def __UpperCamelCase( _A : float , _A : int = 18 , _A : int = 10 ):
'''simple docstring'''
UpperCAmelCase__ : int = angle_in_degrees - ((angle_in_degrees // 3_6_0.0) * 3_6_0.0)
# Converti... | 614 | 1 |
'''simple docstring'''
import math
def __UpperCamelCase( _A : int ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
... | 614 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
fro... | 614 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | '''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMS... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : int = 10 , _A : int = 10_00 , _A : bool = True ):
'''simple docstring'''
assert (
isinstance(_A , _A )
and isinstance(_A , _A )
and isinstance(_A , _A )
), "Invalid typ... | 614 | '''simple docstring'''
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 614 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ : Dict = {
'configuratio... | 614 | '''simple docstring'''
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - gener... | 614 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.model... | 614 | '''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky... | 614 | 1 |
'''simple docstring'''
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import GradientAccumulato... | 614 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rand... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : list ):
'''simple docstring'''
UpperCAmelCase__ : Any = len(_A )
for i in range(1 , _A ):
UpperCAmelCase__ : Union[str, Any] = collection[i]
UpperCAmelCase__ : Any = 0
UpperCAmelC... | 614 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase__ : List[Any] = {
'microsoft/wavlm-base': 'https://huggingface.... | 614 | '''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__ : str = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __UpperCamel... | 614 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testi... | 614 | '''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOK... | 614 | 1 |
'''simple docstring'''
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import ... | 614 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ ... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : str , _A : str ):
'''simple docstring'''
UpperCAmelCase__ : int = len(_A )
UpperCAmelCase__ : int = len(_A )
UpperCAmelCase__ : int = (
first_str_length if first_str_length > se... | 614 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : str = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'... | 614 | 1 |
'''simple docstring'''
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase( _A :... | 614 | '''simple docstring'''
import numpy as np
def __UpperCamelCase( _A : np.ndarray , _A : np.ndarray , _A : float = 1e-12 , _A : int = 1_00 , ):
'''simple docstring'''
assert np.shape(_A )[0] == np.shape(_A )[1]
# Ensure proper dimensiona... | 614 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMi... | 614 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase ,low... | 614 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGe... | 614 | '''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from tra... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase( _A : list[int] , _A : list[int] , _A : int ):
'''simple docstring'''
UpperCAmelCase__ : List[Any] = list(range(len(_A ) ) )
UpperCAmelCase__ : Optio... | 614 | '''simple docstring'''
import baseaa
def __UpperCamelCase( _A : str ):
'''simple docstring'''
return baseaa.baaencode(string.encode('''utf-8''' ) )
def __UpperCamelCase( _A : bytes ):
'''simple docstring'''
return baseaa.baadecode(_A ).decode('''utf-8''... | 614 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common... | 614 | '''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCamelCase__ : Optional[Any] = logging.getLogger(__name__)
Uppe... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : str , _A : str = " " ):
'''simple docstring'''
UpperCAmelCase__ : List[Any] = []
UpperCAmelCase__ : Any = 0
for index, char in enumerate(_A ):
if char == separator:
split_words.append(... | 614 | '''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCamelCase( _A : Any , _A : List[str]=() , _A : List[str]=None ... | 614 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCamelCase__ : Li... | 614 | '''simple docstring'''
from __future__ import annotations
def __UpperCamelCase( _A : list[int] , _A : int , _A : int , _A : int ):
'''simple docstring'''
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[in... | 614 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
UpperCamelCase__ : Union[str, Any] = get... | 614 | '''simple docstring'''
def __UpperCamelCase( _A : float , _A : list[float] ):
'''simple docstring'''
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows list cannot be empty''' )
U... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : int ):
'''simple docstring'''
assert isinstance(_A , _A ), F'''The input value of [n={number}] is not an integer'''
if number == 1:
return 2
elif number < 1:
UpperCAmelCase__ : List[str] = F'''The input value ... | 614 | '''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase( ):
'''simple docstring'''
UpperCAmelCase__ : str = [randint(-10_00 , 10_00 ) for i in range(10 )]
UpperCAmelC... | 614 | '''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging... | 614 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ : Any = {
'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_M... | 614 | '''simple docstring'''
from math import factorial, radians
def __UpperCamelCase( _A : float , _A : int = 18 , _A : int = 10 ):
'''simple docstring'''
UpperCAmelCase__ : int = angle_in_degrees - ((angle_in_degrees // 3_6_0.0) * 3_6_0.0)
# Converti... | 614 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_commo... | 614 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
fro... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : int = 10_00 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ : Optional[int] = 1, 1
UpperCAmelCase__ : Union[str, Any] = []
for i in range(1 , n + 1 ):
UpperCAmelCase__ : str ... | 614 | '''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMS... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase( _A : list[list[int]] ):
'''simple docstring'''
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
f... | 614 | '''simple docstring'''
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 614 | 1 |
'''simple docstring'''
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class _lowercase :
'''simple docstring'''
UpperCAmelCase_ : float
UpperCAmelCase_ : TreeNode | None = None
UpperCAmelCase_ : TreeNode | None = None
... | 614 | '''simple docstring'''
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - gener... | 614 | 1 |
'''simple docstring'''
from numpy import exp, pi, sqrt
def __UpperCamelCase( _A : List[str] , _A : float = 0.0 , _A : float = 1.0 ):
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__... | 614 | '''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : int ):
'''simple docstring'''
UpperCAmelCase__ : Union[str, Any] = [0] * len(_A )
UpperCAmelCase__ : List[Any] = []
UpperCAmelCase__ : Union[str, Any] = [1] * len(_A )
for values in graph.values(... | 614 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rand... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase( _A : int , _A : int ):
'''simple docstring'''
UpperCAmelCase__ : list[list[int]] = []
create_all_state(1 , _A , _A , [] , _A )
return result
def __U... | 614 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
R... | 614 | '''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__ : str = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __UpperCamel... | 614 | 1 |
'''simple docstring'''
UpperCamelCase__ : int = '0.18.2'
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,... | 614 | '''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOK... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__ : List[Any] = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class _lowercase :
'''simple docstring''... | 614 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ ... | 614 | 1 |
'''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging... | 614 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : str = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'... | 614 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET... | 614 | '''simple docstring'''
import numpy as np
def __UpperCamelCase( _A : np.ndarray , _A : np.ndarray , _A : float = 1e-12 , _A : int = 1_00 , ):
'''simple docstring'''
assert np.shape(_A )[0] == np.shape(_A )[1]
# Ensure proper dimensiona... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : Any , _A : int ):
'''simple docstring'''
UpperCAmelCase__ : int = 0
UpperCAmelCase__ : Union[str, Any] = len(_A ) - 1
while left <= right:
# avoid divided by 0 during interpolation
if sor... | 614 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase ,low... | 614 | 1 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__ : str = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __UpperCamel... | 614 | '''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from tra... | 614 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : List[str] = {'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', 'YolosOnnxConfig']}
try:
i... | 614 | '''simple docstring'''
import baseaa
def __UpperCamelCase( _A : str ):
'''simple docstring'''
return baseaa.baaencode(string.encode('''utf-8''' ) )
def __UpperCamelCase( _A : bytes ):
'''simple docstring'''
return baseaa.baadecode(_A ).decode('''utf-8''... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test... | 614 | '''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCamelCase__ : Optional[Any] = logging.getLogger(__name__)
Uppe... | 614 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resiz... | 614 | '''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCamelCase( _A : Any , _A : List[str]=() , _A : List[str]=None ... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__ : Optional[Any] = 'Muhammad Umer Farooq'
UpperCamelCase__ : Optional[Any] = 'MIT'
UpperCamelCase__ : int = '1.0.0'
UpperCamelCase__ : int = 'Muhammad Umer Farooq'
UpperCamelCase__ : ... | 614 | '''simple docstring'''
from __future__ import annotations
def __UpperCamelCase( _A : list[int] , _A : int , _A : int , _A : int ):
'''simple docstring'''
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[in... | 614 | 1 |
'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, Sin... | 614 | '''simple docstring'''
def __UpperCamelCase( _A : float , _A : list[float] ):
'''simple docstring'''
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows list cannot be empty''' )
U... | 614 | 1 |
'''simple docstring'''
import numpy as np
def __UpperCamelCase( _A : np.ndarray , _A : np.ndarray , _A : float = 1e-12 , _A : int = 1_00 , ):
'''simple docstring'''
assert np.shape(_A )[0] == np.shape(_A )[1]
# Ensure proper dimensiona... | 614 | '''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 614 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def __UpperCamelCase( _A : NDArray[floataa] , _A : NDArray[floataa] , _A : list[int] , _A : int , ):
'''simple d... | 614 | '''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging... | 614 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowercase ( metaclass=lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = ['''note_seq''']
def __init__( self ,*lowerCamelCase_ ,**lowerCamelCase_ ... | 614 | '''simple docstring'''
from math import factorial, radians
def __UpperCamelCase( _A : float , _A : int = 18 , _A : int = 10 ):
'''simple docstring'''
UpperCAmelCase__ : int = angle_in_degrees - ((angle_in_degrees // 3_6_0.0) * 3_6_0.0)
# Converti... | 614 | 1 |
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCamelCase( _A : Any , _A : List[str]=() , _A : List[str]=None ... | 614 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
fro... | 614 | 1 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when swit... | 614 | '''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMS... | 614 | 1 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __UpperCamelCase( _A : Dict , _A : Optional[Any] , _A : List[Any]=None , **_A : List[str] ):
'''simple docstring'''
UpperCAmelCase__ : List[str] = [x.... | 614 | '''simple docstring'''
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 614 | 1 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__ : Any = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCamelCase( _A : list[list[int]] , _A : list[int] , _A : list[int] , _A ... | 614 | '''simple docstring'''
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - gener... | 614 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 614 | '''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky... | 614 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def __UpperCamelCase( _A : in... | 614 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rand... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : int , _A : int ):
'''simple docstring'''
while second != 0:
UpperCAmelCase__ : Dict = first & second
first ^= second
UpperCAmelCase__ : Tuple = c << 1
return first
if __name__ == "__main_... | 614 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | 1 |
'''simple docstring'''
def __UpperCamelCase( _A : int = 10 ):
'''simple docstring'''
if not isinstance(_A , _A ) or n < 0:
raise ValueError('''Invalid input''' )
UpperCAmelCase__ : Optional[int] = 10**n
UpperCAmelCase__ : Union[str, Any] = 2_84_33 * ... | 614 | '''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__ : str = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __UpperCamel... | 614 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ ... | 614 | '''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOK... | 614 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase( _A : List[str] )... | 614 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ ... | 614 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase__ : Optional[int] = logging.get_logger(__name__)
class _lowercase ( l... | 614 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : str = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'... | 614 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Optional[Any] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/... | 614 | '''simple docstring'''
import numpy as np
def __UpperCamelCase( _A : np.ndarray , _A : np.ndarray , _A : float = 1e-12 , _A : int = 1_00 , ):
'''simple docstring'''
assert np.shape(_A )[0] == np.shape(_A )[1]
# Ensure proper dimensiona... | 614 | 1 |
'''simple docstring'''
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing i... | 614 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase ,low... | 614 | 1 |
'''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from tra... | 614 | '''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from tra... | 614 | 1 |
'''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase ,low... | 614 | '''simple docstring'''
import baseaa
def __UpperCamelCase( _A : str ):
'''simple docstring'''
return baseaa.baaencode(string.encode('''utf-8''' ) )
def __UpperCamelCase( _A : bytes ):
'''simple docstring'''
return baseaa.baadecode(_A ).decode('''utf-8''... | 614 | 1 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.confi... | 0 | '''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCamelCase__ : Optional[Any] = logging.getLogger(__name__)
Uppe... | 614 | 0 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import Tokenize... | 1 | '''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCamelCase( _A : Any , _A : List[str]=() , _A : List[str]=None ... | 614 | 0 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def SCREAMING_SNAKE_CASE_ ( _snake_case :Any ) -> Optional[int]:
return getitem, k
def SCREAMING_SNAKE_CASE_ ( _snake_case :Dict , _snake_case :int ) -> ... | 2 | '''simple docstring'''
from __future__ import annotations
def __UpperCamelCase( _A : list[int] , _A : int , _A : int , _A : int ):
'''simple docstring'''
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[in... | 614 | 0 |
'''simple docstring'''
def A_( A : list):
for i in range(len(A) - 1 , 0 , -1):
UpperCamelCase = False
for j in range(A , 0 , -1):
if unsorted[j] < unsorted[j - 1]:
UpperCamelCase , Up... | 3 | '''simple docstring'''
def __UpperCamelCase( _A : float , _A : list[float] ):
'''simple docstring'''
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
raise ValueError('''Cash flows list cannot be empty''' )
U... | 614 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : str ):
lowerCAmelCase ,lowerCAmelCase = analyze_text(_UpperCAmelCase )
lowerCAmelCase = list(' '... | 4 | '''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 614 | 0 |
'''simple docstring'''
import pytest
_lowercase = """__dummy_dataset1__"""
_lowercase = """
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \... | 5 | '''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging... | 614 | 0 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_torc... | 6 | '''simple docstring'''
from math import factorial, radians
def __UpperCamelCase( _A : float , _A : int = 18 , _A : int = 10 ):
'''simple docstring'''
UpperCAmelCase__ : int = angle_in_degrees - ((angle_in_degrees // 3_6_0.0) * 3_6_0.0)
# Converti... | 614 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {
'''configuration_upernet''': ['''UperNetConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailab... | 7 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
fro... | 614 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> list:
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('The given input must be positive' )
# get the generated string sequence
... | 8 | '''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMS... | 614 | 0 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {'''vocab_file''': '''vocab.txt'''}... | 9 | '''simple docstring'''
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 614 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers... | 10 | '''simple docstring'''
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - gener... | 614 | 0 |
'''simple docstring'''
import warnings
from ..trainer import Trainer
from ..utils import logging
lowercase_ = logging.get_logger(__name__)
class __A ( A ):
'''simple docstring'''
def __init__(self , A=None , **A ) -> str:
"""simple docstring"""
... | 11 | '''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky... | 614 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... | 12 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rand... | 614 | 0 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datacla... | 13 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise Optional... | 14 | '''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__ : str = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __UpperCamel... | 614 | 0 |
from PIL import Image
def UpperCamelCase ( __magic_name__ : Image , __magic_name__ : float ) -> Image:
"""simple docstring"""
def brightness(__magic_name__ : int ) -> float:
return 128 + level + (c - 128)
if not -2_5_5.0 <= level <= 2_5_5.0... | 15 | '''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOK... | 614 | 0 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
__A : Union[str, Any] = logging.getLogger()
... | 16 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class _lowercase ( lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase_ ... | 614 | 0 |
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
UpperCAmelCase_ : Optional[Any] = models.Sequential()
# S... | 17 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : str = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'... | 614 | 0 |
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __a(SCREAMING_SNAKE_CASE_ : List[Any] , SCREAMING_SNAKE_CASE_ : Optional[int]=() ... | 18 | '''simple docstring'''
import numpy as np
def __UpperCamelCase( _A : np.ndarray , _A : np.ndarray , _A : float = 1e-12 , _A : int = 1_00 , ):
'''simple docstring'''
assert np.shape(_A )[0] == np.shape(_A )[1]
# Ensure proper dimensiona... | 614 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
"""micros... | 19 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _lowercase ( lowerCAmelCase ,low... | 614 | 0 |
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